Exercise

Random Forest: modeling

Like gradient boosted trees, random forests are another form of ensemble model. That is, they use lots of simpler models (decision trees, again) and combine them to make a single better model. Rather than running the same model iteratively, random forests run lots of separate models in parallel, each on a randomly chosen subset of the data, with a randomly chosen subset of features. Then the final decision tree makes predictions by aggregating the results from the individual models.